Cryocrystallography is the collection of crystallographic data at cryogenic temperatures primarily with the use of liquid nitrogen. The following advantages and disadvantages are comparing cryogenic vs. room temperature data collection.
Advantages
1) Reduced Radiation Damage: when compared to room temperature collection
2) Fewer Crystals: as to be expected if the radiation damage is reduced the crystal lifetime is increased therefore reducing number of crystals
3) Better Data: increased resolution, I/sigma, redundancy, reduced B values and stronger anomalous signal
4) Better Crystals: protein crystals can be selected at opportune times during the crystallization process (possibly avoid dissolving or cracking) as well as be easily transported within cryogenic dewars
Disadvantages
1) Icing: even if icing occurs it may be possible to salvage the collection during data processing
2) Cryoprotectants: many protein crystals require the use of a cryoprotectant (the most popular is the use of 20-25 % glycerol) prior to being exposed to the cold stream
3) Increased mosaicity: this can be reduced with the proper cryoprotectant as well as mounting technique (ref pg. 32)
4) Non-isomorphism: unit cell size may vary (ref)
5) Cost of equipment: include in grant applications or have at least two bake sales
We have doubled the number of resources in our tool page over the past couple of weeks. The focus has been on trying to bring together websites that are useful for macromolecular crystallography.
If there is a resource that we are missing and you’ve found it helpful, feel free to leave a comment.
Neutron crystallography can be used to gain insight into hydrogen positions. This is extremely beneficial when trying to determine a mechanism. This was the case for endothiapepsin. If one is able to substitute hydrogen for deuterium, the scattering is significantly increased (see slide 14 of Roger Pynn’s presentation on Neutron Crystallography Theory). Deuterons scatter neutrons in a manner similar to that of carbon. In X-ray crystallography, however, we see that they are quite different.
Two methods are used to exchange hydrogens:
1) The crystal can be soaked in deuterated buffer or by placing deuterated water at the ends of the capillary to allow for vapor exchange.
2) The protein can be expressed by using perdueterated media, in which the carbon source for E. coli contains deuterium. Check with your favorite neutron beam line to find out if they offer perdeuteration services. Perdeuteration is the ideal method because nearly all hydrogens can be exchanged. The only downside here is that you may not be able to use the exact same crystallization conditions as the native protein.
If you are considering using neutron crystallography, I would suggest using these two general criteria based on previous published neutron structures.
1) Crystal size ~1 mm^3 or larger
2) Crystal has been solved to ~1 A or better with X-rays
Recently, a nice summary figure and table have been published. They show the current parameters of neutron structures that have been published up to 2007.
Data collection time can be greatly reduced if your crystal is in a high symmetry. High symmetry is a significant benefit in neutron crystallography since it may take 12 hours to collect a frame (mileage will vary depending on beam line).
Finally, it has been proposed that Oak Ridge be able to reduce crystal size to 0.1 mm^3 (pdf). If this is made possible, we may see neutron crystallography becoming a more routine crystallographic technique.
BRENDA is a gold mine for those studying enzymes! The database proclaims to be the comprehensive enzyme information system and with 5010 enzymes it looks to be the case. Here is a screenshot of the navigation bar. As you can see BRENDA brings together many different categories such as IC50 values, pH stability range and crystallization.
My only suggestion so far is to change ‘Recommended Name’ to ‘Enzyme name’. I think it would save some confusion in the search entry.
I have never seen another database bring together this much information about a class of proteins. If you have a colleague working in enzymology this is site is definitely worth passing along.
At the beginning of the year, we discussed whether the CCP4bb should become a forum. Initially, BioKlatch.com was created by Matt Harrington – the site is now being redirected to MajorGroove.org.
The site is based on StackExchange, which is a new website designed around a simple question and answer format. It will be interesting to see if the pricing changes once the site is out of beta. The site includes a number of community features. On example: the ability to earn badges by performing various activities, from filling out your profile to posing a good question.
The discussions are still kept on the CCP4bb, but the answers/responses are then posted on MajorGroove.org. If the system works well, it should provide an extensive selection of Q&A that have previously been addressed on the CCP4bb.
Are you excited about this new resource? Is this just one more place to visit? I have joined, will you?
For structural information concerning metals and RNA then you may find MeRNA quite helpful (pdf ref). Metals have been shown to play an important role in RNA folding. The MeRNA database currently contains 398 PDB entries which include 22 different metals.
Note: The MESPEUS database is excellent resource for metals and proteins.
The simple periodic table display works well. The results page would be easier to read if the titles were not all in italics.
The advance search offers a number of function with my favorite being the ability to search through 8 different binding motifs. The advanced search also allows for search by reference and/or author.
Phenix (Python-based Hierarchical ENvironment for Integrated Xtallography) has been developed for the determination of macromolecular crystallographic structures. Phenix is a leader in automating the structure determination process.
I am going to start playing around with Phenix, but first wanted bring together helpful resources about the program suite:
This is a follow up to the post Is the Beam Center Correct? which shows how to determine if your beam center is correct. Today, we will be looking at how correct the beam center if it is wrong.
The computer screen is not as clear as I would like, but think you will be able to follow along (watching the video full screen should help). The audio is a little hard to hear at the end since I am speaking directly behind the camera. Anyway, I would love to hear your thoughts.
Here is the post on the format of a comm file. We also had a post on the overview of using ipmosflm, which should help you follow along with this post if you get stuck. When I bring up ‘previous set’ am referring to the offset seen in the Is the Beam Center Correct? video.
I would love to hear some feedback on this! Can you follow along? Do you like having videos? I would also love hear suggestions on screen recording software (linux or windows).
We have had a couple of instances when the beam center was incorrect in the header of our images. The header of an image is written out when you collect a diffraction image. The header may contain the wavelength, collection time, beam center and oscillation step size, which are read by data processing software (in this case Ipmosflm).
Unfortunately, the information contained within the header may not be correct.
How can you look for to tell if your beam center is incorrect?
One way is by looking at where the Bragg reflections are predicted vs. where they actually are located. It is important to check if the orientation of the lunes and the spacing between Bragg reflections looks reasonable. If they are not then you may an issue with your unit cell and/or space group and not a beam center problem.
If you are having trouble seeing the offset in the video here is a screen shot:
The blue arrow is pointing toward the Bragg reflections while the red arrow indicates the predicted reflection locations. Also you can see that there are fewer Bragg reflections (dark spots) than what is predicted (yellow squares) which is a sign that there is a problem.
CNS (Crystallography and NMR systems) is able to perform simulated annealing to get started, one must first create a generate file.
1) Input then scroll down to Refinement, refine.inp and Edit
2) amy.pdb needs to be replaced with your pdb file
3) The space group, unit cell, angles and amy.cv need to be updated
4) Adjust the resolution to your desired range. The overall B-factor correction should be set to isotropic unless you are dealing with very high resolution data (~1 Angstrom). Set Bulk solvent correction needs to be set to False
5) Change annealing schedule to slowcool
Note: Not shown, but I usually set the map grid to 0.25 for better viewing
Save an updated file
In your terminal:
type: cns < refine.inp > refine.out &
Note: if you renamed your generate files then use them as your .inp
The ‘&’ symbol allows your cursor to be free
type: tail -f refine.out
This will allow to see the progress of the processing in your terminal
This allows you to quickly see if the inputs have generate an error
